Screening For A Mammogram

Breast cancer-detecting AI is 20 per cent more effective than radiologists

Image credit: ORION PRODUCTION Shutterstock

An artificial intelligence (AI) programme has been developed that can diagnose more cases of breast cancer from mammography screenings than radiologists.

The AI tool is considered to be a safe alternative to conventional double reading by radiologists and can reduce heavy workloads for doctors.

In a randomised controlled trial led by researchers from Lund University in Sweden, 80,033 women were randomly allocated into two groups: 40,003 women in the intervention group that underwent AI-supported screening and 40,030 in the control group that underwent standard double reading without AI support.

“In our trial, we used AI to identify screening examinations with a high risk of breast cancer, which underwent double reading by radiologists. The remaining examinations were classified as low risk and were read only by one radiologist. In the screen reading, radiologists used AI as detection support, in which it highlighted suspicious findings on the images,” said Kristina Lång, who led the study.

“We found that using AI resulted in the detection of 20 per cent more cancers compared with standard screening, without affecting false positives. A false positive in screening occurs when a woman is recalled but cleared of suspicion of cancer after workup.”

At the same time, the screen-reading workload for radiologists was reduced by 44 per cent. The number of screen readings with AI-supported screening was 46,345 compared with 83,231 with standard screening.

On average, a radiologist reads 50 screening examinations an hour. Using the new AI, the researchers estimated that it took approximately five months less of a radiologist’s time to read the 40,000 screening examinations in the AI group.

“The study was conducted on a single site in a Swedish setting. We need to see whether these promising results hold up under other conditions, for example with other radiologists or other AI algorithms,” Lång said. “There may be other ways to use AI in mammography screening, but these should preferably also need to be investigated in a prospective setting,” 

A total of 100,000 women have now been enrolled in the trial. The research team’s next step is to investigate which cancer types were detected with and without AI support.

The interval-cancer rate will be assessed after the 100,000 women in the trial have had at least a two-year follow-up. An interval cancer is a cancer diagnosed between screenings and generally has a poorer prognosis than screen-detected cancer. 

“Just because a screening method finds more cancers does not necessarily mean it’s a better method,” Lång said.

“What’s important is to find a method that can identify clinically significant cancers at an early stage. However, this has to be balanced with the harm of false positives and the overdiagnosis of indolent cancers. The results from our first analysis shows that AI-supported screening is safe since the cancer detection rate did not decline despite a substantial reduction in the screen-reading workload.”

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